1. Field of the Invention
The present invention relates to information handling systems, and more particularly to improving image artifact detection in video quality benchmarks.
2. Description of the Related Art
As the value and use of information continues to increase, individuals and businesses seek additional ways to process and store information. One option available to users is information handling systems. An information handling system generally processes, compiles, stores, and/or communicates information or data for business, personal, or other purposes thereby allowing users to take advantage of the value of the information. Because technology and information handling needs and requirements vary between different users or applications, information handling systems may also vary regarding what information is handled, how the information is handled, how much information is processed, stored, or communicated, and how quickly and efficiently the information may be processed, stored, or communicated. The variations in information handling systems allow for information handling systems to be general or configured for a specific user or specific use such as financial transaction processing, airline reservations, enterprise data storage, or global communications. In addition, information handling systems may include a variety of hardware and software components that may be configured to process, store, and communicate information and may include one or more computer systems, data storage systems, and networking systems.
One use of information handling systems is presenting video such as high-definition video. An issue relating to presenting high-definition video on information handling systems relates to when high-definition video is distributed across a network such as wired and wireless networks. To deliver products with the level of quality and clarity that customer's desire, it is desirable to provide video quality measurement tools that provide video quality information in addition to frames-per-second information.
There are a number of issues relating to providing meaningful video quality information. For example, meaningful video quality information should accurately reflect end user experience. There is a movement in the information handling industry to define a set of performance metrics that would more accurately reflect end user experience. Known video quality measurement tools assess image and motion quality but the image quality assessment does not truly reflect end user perception.
For example, end users perceive picture defects in perceptually salient screen areas more critically than those in less important regions. Known video quality measurement tools fail to consider the perceptual impact of a defect's location. For example, artifacts of similar intensity on an image yield the same video quality score whether the artifacts occur at the edge of the screen or over a perceptually important region.
Accordingly, it would be desirable to provide a video quality measurement that appreciates and quantifies a difference between mathematically similar artifacts that have different effects on user perception.